In range-based location determination systems, time delay measurements of ranging signals from a plurality of sources are converted to range information associated with the source of each ranging signal. Ranges to different sources with known locations are combined to solve for the unknown user location via geometric techniques known, for example, as trilateration (triangulation). If delay of ranging signals cannot be known reliably (e.g. in asynchronous systems where the user clock is not synchronized to the network), location determination algorithms may treat user clock temporal bias as another unknown, to be solved for by the trilateration process, using an additional ranging measurement.
In location determination systems, measured user distances to a plurality of sources with known locations are combined to solve for the unknown user location via geometric techniques, for example: advanced forward link trilateration (AFLT). AFLT typically requires that the number of measurements available be at least equal to the number of unknown coordinates in the system, including the mobile spatial coordinates and time bias. Typically, multiple ranging signals from a given terrestrial source are available, due to a variety of factors such as antenna sectorization, antenna diversity at the source or receiver (spatial diversity), multiple transmissions of the ranging signal at the source (temporal diversity), and the existence of multi-path. As another example of this technique, multiple ranging signals from orbiting navigation satellites, such as GPS, GLONASS, and Galileo, may be used for location determination of a mobile user.
In prior art location estimation schemes, the ranging signal set is filtered to select a single measurement from each source that is deemed most accurate via a predetermined threshold. In addition, the filtered ranging signal set may be further filtered (i.e., with reduced ranging signal set dimensionality) to exclude single ranging signals from a given source where that single ranging signal is deemed insufficiently accurate or its source is deemed unreliable.
On the one hand, a priori ranging signal filtering can improve statistical confidence in the computed location determination solution due to the exclusion of what is deemed as unreliable ranging signals. However, in some cases, this a priori filtering can lead to accidental exclusion of good ranging signals which may ultimately degrade the accuracy of the location determination solution. In certain scenarios, retention of multiple ranging measurements from each signal source (i.e., using unfiltered ranging signals in the position determination algorithm) may result in improved position determination accuracy
Accordingly, it is desirable to provide a method for selecting a location determination solution from a set of possible location determination solutions generated from filtered and unfiltered ranging signals to improve accuracy.